Electrical impedance tomography (hereinafter “EIT”) is a known technique for non-invasive spatial mapping of the electrical resistance (referred to by use of the more general term “impedance”) of internal body tissues. The tissue impedance varies with tissue type and health, and it also varies temporally, on the order of 10 milliseconds (ms) or less, as a result of electrical activity occurring within the body tissues. A particularly important source of electrical activity in the body is the brain, and the present invention is particularly focused on EIT used to map the impedance of tissues associated with the brain, e.g., cortex (white and gray matter), cerebrospinal fluid, skull, and scalp.
In ordinary EIT used as a tool for probing the brain, an array of electrodes is applied to the head surface. Typically, the array consists of 256 electrodes, and it is desirable to provide as many electrodes as is practical, i.e., it is desirable to have a “dense” array.
Each electrode is used to “inject” an electrical current into the head, i.e., into the tissues the impedances of which it is desired to ascertain, and the remaining electrodes are used to measure the spatial distribution of the resulting electrical potentials that arise at the surface of the head.
Determining the internal tissue impedances responsible for the measured potentials in view of the known injected currents is an example of what is well known in the art as an “inverse problem.” An inverse problem is generally to deduce unknown structure in view of the structure's known responses to known stimuli. To “solve” an inverse problem is generally to hypothesize a mathematical model for the unknown structure, test the model by applying the known stimuli mathematically to determine whether its output agrees with those actually measured, assess the error, adjust the model to try to reduce the error, and iterate these steps until a convergence is obtained that represents an optimum solution.
Inverse problems are generally “ill-posed,” or ambiguous, so that it is generally understood to be important to “constrain” the iterative solution process by known relevant facts. One way of constraining the solutions is to provide for greater resolution in the data, which is the reason for preferring the dense array. Also, typically, for solving inverse problems associated with probing internal anatomy such as the brain, anatomical constraints are utilized, such as may be obtained by magnetic resonance imaging (MRI).
EIT is used herein as a generic term that includes ordinary EIT as well as magnetic resonance EIT, or “MREIT.” MREIT is also a known technique in which a magnetic resonance (“MR”) image is obtained of the injected currents, from which the current density can be determined, which in turn allows for determining impedance.
MREIT does not require solving an inverse problem, and its spatial resolution is superior to that of EIT. On the other hand, EIT does not require use of an expensive MR imaging machine.
EIT has also been considered as a tool for imaging dynamic neural functions in the brain. When neurons “fire” (i.e., depolarize), they transfer ions into the extracellular space, decreasing their soma size and cross-section for conducting current, decreasing their electrical impedance. Conversely, when the neurons polarize they absorb ions from the extracellular space, increasing their soma size and cross-section for conducting current, increasing their electrical impedance. Once the ordinary EIT inverse problem has been solved, i.e., once a satisfactory model of the static impedances has been identified, the same model can in principle be used to very quickly localize changes in impedance associated with neural function. Unfortunately, the impedance changes are too small to be reliably discerned, and EIT is not considered to be a useful imaging modality.
Electroencephalography (“EEG”) measures the electrical activity of the brain. When neural activity (the ongoing synaptic effects) changes the polarization of the soma of pyramidal neurons of the cortex (which are aligned and therefore create far fields), there is a change in the polarity between the soma at the apical dendrites (toward the surface of the cortex). For example, greater negativity at the soma leads to relative positivity at the apical dendrites, creating a dipole and thus a dipolar field. These dipoles are referred to as “sources,” and EEG is used to localize the sources. In EEG, an array of electrodes is applied to the head surface, and each electrode is used to measure electrical potentials that arise at the surface of the head in response to source activity.
EEG source localization also presents an inverse problem, so again, it is particularly desirable to provide a dense array for EEG (dEEG). The inverse problem is particularly to deduce the locations and relatives strengths of the sources as would be needed to produce the measured distribution of surface potentials, and it is solved in the same general manner indicated above.
While EEG is a standard brain imaging tool, any tool that requires solving an inverse problem will have limited capability. Recognizing this, the present inventor developed the method described in U.S. Patent Publication No. 20030093005, which combines images produced by EEG and MRI to enhance resolution.